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Assessing Rainfall-EVI Relationships in the Okavango Catchment Employing MODIS Time Series Data and Distributed Lag Models

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Book cover Remote Sensing Time Series

Part of the book series: Remote Sensing and Digital Image Processing ((RDIP,volume 22))

Abstract

Aboveground net primary productivity (ANPP) is limited by water availability especially in dry and desert regions, and many studies have linked ANPP to current and previous “effective” rainfall events. In this study a distributed lag model (DLM) was used to assess the impact of current and previous 16 day rainfall anomalies on the Enhanced Vegetation Index (EVI) as a proxy for ANPP in the Okavango catchment (South Africa). The two important aspects in using DLMs are the explained total ANPP variability by the rainfall regime and the duration of that dependency. The results indicate that more than 50 % of the Okavango Basin are sensitive towards current and previous rainfall anomalies. These regions are mainly restricted to the southern semi-arid parts of the catchment, whereas in the humid and sub-humid northern areas significant correlations were observed only locally. Here, the dominant land cover classes are shrub- and grassland, thornbush savannahs and mixed woodlands. The duration of significant rainfall-EVI dependencies ranges from concurrent anomalies to a time-shift of 3.5 months. A logistic regression model was applied to discriminate among the sensitive and non-sensitive areas in the basin in terms of possible physiogeographic covariates. The model was able to correctly classify ~80 % of the available pixels. Most relevant explanatory covariates were evaporation, elevation and land cover.

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Acknowledgements

This study was partially conducted within the “Future Okavango” project funded by the German Federal Ministry of Education and Research (BMBF) in the frame of the funding measure “Sustainable Land Management”. This support is gratefully acknowledged. The authors would also like to thank NASA/PPS for providing the MODIS imagery and the TRMM data, as well as the Climate Service Center, Helmholtz-Zentrum Geesthacht, especially Dr. Torsten Weber, for providing evaporation data.

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Authors and Affiliations

  1. Environmental Remote Sensing and Geoinformatics, Faculty of Regional and Environmental Sciences, University of Trier, Trier, Germany

    Thomas Udelhoven, Marion Stellmes & Achim Röder

Authors
  1. Thomas Udelhoven
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  2. Marion Stellmes
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  3. Achim Röder
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Correspondence to Thomas Udelhoven .

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Editors and Affiliations

  1. German Remote Sensing Data Center, DFD, German Aerospace Center, DLR, Wessling, Germany

    Claudia Kuenzer

  2. German Remote Sensing Data Center, DFD, German Aerospace Center, DLR, Wessling, Germany

    Stefan Dech

  3. Department of Geodesy and Geoinformation, Vienna University of Technology, Vienna, Austria

    Wolfgang Wagner

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Udelhoven, T., Stellmes, M., Röder, A. (2015). Assessing Rainfall-EVI Relationships in the Okavango Catchment Employing MODIS Time Series Data and Distributed Lag Models. In: Kuenzer, C., Dech, S., Wagner, W. (eds) Remote Sensing Time Series. Remote Sensing and Digital Image Processing, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-15967-6_11

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